What are graphics processing units (GPUs) and compute infrastructure?

A graphics processing unit (GPU) is a specialized processor that can perfom many calculations at the same time, making it especially useful for demanding workloads such as AI and machine learning (ML) workloads. Compute infrastructure is the broader collection of processing power, servers, memory, storage, and networking needed to run those workloads.

How do GPUs and compute infrastructure work?

GPUs handle large numbers of calculations in parallel. Compute infrastructure, more generally, provides the processing, memory, storage, and connectivity needed to train and run AI models.

Why are GPUs and compute infrastructure important?

The right GPUs and compute infrastructure can improve the speed, performance, and cost-efficiency of AI workloads. As AI is embedded into more business systems, organizations will need more computing power to keep up with growing demand.

Benefits and use cases

• Faster model training and inference
• Elastic scaling for AI workloads
• Cost optimization across environments
• Support for retrieval-augmented generation (RAG), natural language processing (NLP), and computer vision pipelines

Does NexusTek help with GPU and compute infrastructure?

Yes. NexusTek enables customers to operationalize AI and cloud faster and more securely, helping architect and manage the infrastructure foundation needed to scale with confidence across hybrid and multi-cloud environments.